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# Copilot Instructions for sec-certs
## Repository Overview
**sec-certs** is a Python data scraping and analysis tool for security certificates from Common Criteria (CC) and FIPS 140-2/3 frameworks. The tool processes certification artifacts (PDFs, HTML), extracts data, matches to CVEs/CPEs, and provides datasets for security research.
### Tech Stack
- **Language**: Python 3.10+ (tested on 3.10, 3.11, 3.12)
- **Size**: ~75 Python source files (~13.5k LOC), ~36 test files
- **Package Management**: uv with pinned requirements in `uv.lock`
- **Key Dependencies**: BeautifulSoup4, pandas, spacy, pdftotext (requires Poppler), pikepdf, pytesseract, scikit-learn, matplotlib, networkx, pydantic
- **Build System**: setuptools with setuptools-scm for versioning
- **Testing**: pytest with custom markers (`slow`, `remote`)
- **Linting**: Ruff (formatter + linter) and MyPy (type checking)
- **Documentation**: Sphinx with myst-nb, hosted at sec-certs.org
- **Distribution**: PyPI package and DockerHub image
## Critical Setup Requirements
### System Dependencies (REQUIRED)
**ALWAYS install these system dependencies before pip packages. Code WILL fail without them:**
- **Poppler** (≥20.x): Required by pdftotext library. Older 0.x versions WILL fail.
- **Tesseract**: Required for OCR of malformed PDFs (with English, French, and German data).
- **Java**: Required to parse tables in FIPS PDF documents. Must be in PATH. Used by `tabula-java` via `tabula-py`.
Check the installation via:
```bash
pdftotext -v
tesseract --version
java -version
```
#### Ubuntu/Debian Installation
For Ubuntu/Debian systems, run:s
```bash
sudo apt-get update
sudo apt-get install -y \
build-essential \
libpoppler-cpp-dev \
pkg-config \
python3-dev \
tesseract-ocr tesseract-ocr-eng tesseract-ocr-deu tesseract-ocr-fra \
default-jdk
```
### Python Environment Setup
**The version file `src/sec_certs/_version.py` is auto-generated by setuptools-scm and must NOT be committed.**
If missing during development, create a temporary version: `echo '__version__ = "dev"' > src/sec_certs/_version.py`
**Development install (for testing and development):**
```bash
# Create a virtual environment
uv venv
# Install all dependencies (including dev ones) and the project in editable mode
uv sync --dev
# ALWAYS download the spacy language model after install
uv run spacy download en_core_web_sm
# Optionally, you can activate the virtual environment and avoid all the "uv run" prefixes
source .venv/bin/activate
```
Verify the installation (sec-certs and spacy language model) by importing the package:
```python
import sec_certs._version
print(sec_certs._version.__version__)
import spacy
print(spacy.load("en_core_web_sm"))
```
## Build, Test, and Validation
### Running Tests
**Basic test run (excludes remote/flaky tests):**
```bash
uv run pytest tests -m "not remote" -v
```
**Test with coverage (as in CI):**
```bash
uv run pytest --cov=sec_certs -m "not remote" --junitxml=junit.xml tests
```
**Test markers:**
- `slow`: Tests that take significant time (run with `-m "slow"` or exclude with `-m "not slow"`)
- `remote`: Tests requiring remote resources (flaky, run weekly via cron workflow)
- `xfail`: Known flaky tests due to external server errors
**Typical test runtime**: Fast tests complete in seconds. Full suite will take minutes.
### Linting and Code Quality
**ALWAYS run these before committing. CI will fail if they don't pass.**
**Using pre-commit (recommended):**
```bash
uv run pre-commit install
uv run pre-commit run --all-files
```
**Manual linting:**
```bash
# Ruff linting (checks code style, imports, complexity)
uv run ruff check .
# Ruff with auto-fix
uv run ruff check . --fix
# Ruff formatting check
uv run ruff format --check .
# Ruff auto-format
uv run ruff format .
# MyPy type checking
uv run mypy .
```
**Linting configuration**: See `pyproject.toml` for Ruff and MyPy settings. Target Python 3.10. Line length: 120. Notebooks (*.ipynb) are excluded from linting.
### Building Documentation
```bash
cd docs
uv run make html
```
Output goes to `docs/_build/html/`. Documentation uses Sphinx with myst-nb for Markdown and Jupyter notebooks.
### Building for Distribution
```bash
uv build
```
This creates source and wheel distributions in `dist/`.
## Project Architecture
### Directory Structure
```
sec-certs/
├── src/sec_certs/ # Main package source
│ ├── dataset/ # Dataset classes (CCDataset, FIPSDataset, etc.)
│ ├── sample/ # Certificate classes (CCCertificate, FIPSCertificate)
│ ├── heuristics/ # Heuristic extractors and analyzers
│ ├── model/ # ML models for matching and NLP
│ ├── utils/ # Utility functions
│ ├── serialization/ # JSON schemas and serialization
│ ├── data/ # Embedded data (annotations, CPEs, etc.)
│ ├── cli.py # Click-based CLI entrypoint
│ ├── configuration.py # Pydantic config with env var support
│ ├── rules.yaml # Regular expressions for cert parsing
│ └── constants.py # Constants and enums
├── tests/ # Test suite
│ ├── cc/ # Common Criteria tests
│ ├── fips/ # FIPS 140 tests
│ ├── data/ # Test fixtures and data
│ └── conftest.py # Pytest configuration and fixtures
├── docs/ # Sphinx documentation source
├── notebooks/ # Jupyter notebooks (examples, analysis)
├── pyproject.toml # Package metadata, build config, tool settings
├── .pre-commit-config.yaml # Pre-commit hooks configuration
├── Dockerfile # Docker image for reproducible environment
└── uv.lock # uv lockfile with pinned dependendices.
```
### Key Files and Configurations
- **pyproject.toml**: Package definition, dependencies, Ruff/MyPy/pytest config. Single source of truth for dependencies (unpinned).
- **src/sec_certs/rules.yaml**: Regular expressions for extracting data from certificates. Add patterns here.
- **src/sec_certs/configuration.py**: Runtime configuration using pydantic-settings. Reads from env vars with `SECCERTS_` prefix.
- **.pre-commit-config.yaml**: Defines pre-commit hooks (ruff, mypy). Versions should match pyproject.toml.
### Main Components
1. **Datasets** (`src/sec_certs/dataset/`):
- `CCDataset`, `FIPSDataset`, `ProtectionProfileDataset`: Main dataset classes
- `CPEDataset`, `CVEDataset`: Auxiliary datasets from NVD
- Load from JSON, web snapshots, or build from scratch
2. **Certificates** (`src/sec_certs/sample/`):
- `CCCertificate`, `FIPSCertificate`: Individual certificate representations
- Store metadata, extracted text, heuristics, references, CVEs
3. **CLI** (`src/sec_certs/cli.py`):
- Entrypoint: `sec-certs {cc|fips|pp} {all|build|download|convert|analyze} [options]`
- Actions: `all` (full pipeline), `download` (fetch certs), `convert` (PDFs to text), `analyze` (extract features)
4. **Heuristics** (`src/sec_certs/heuristics/`):
- Extract certification metadata (dates, vendors, products, security levels)
- CVE/CPE matching and vulnerability analysis
## CI/CD Pipelines
### GitHub Workflows (`.github/workflows/`)
1. **tests.yml** (runs on every push):
- Tests on Python 3.10, 3.11, 3.12 (Ubuntu 22.04)
- Installs system deps, test_requirements.txt, spacy model
- Runs: `pytest --cov=sec_certs -m "not remote" tests`
- Uploads coverage to Codecov
2. **pre-commit.yml** (runs on every push):
- Runs pre-commit hooks (Ruff, MyPy) on all files
- Fails if linting issues found
3. **docs.yml** (runs on push, release):
- Builds Sphinx docs with `cd docs && make html`
- Uploads to sec-certs.org on main branch or tag push
4. **release.yml** (triggered by GitHub release):
- Builds package with `python -m build`
- Publishes to PyPI
- Builds multi-arch Docker image (amd64, arm64) and pushes to DockerHub
5. **cron.yml** (weekly, Wednesday midnight):
- Runs remote/flaky tests with `-m "remote"`
- Continue on error (expected to be flaky)
## Common Workflows
### Adding a New Feature
1. Create branch from `main` (only stable branch for PRs)
2. Make minimal code changes
3. Add tests in appropriate `tests/` subdirectory
4. Run linters: `uv run pre-commit run --all-files` or `uv run ruff check . && uv run mypy .`
5. Run tests: `uv run pytest tests -m "not remote" -v`
6. Update docs if public API changed
7. Commit and push (CI will validate)
### Updating Dependencies
```bash
# Edit pyproject.toml to add/update dependency
# Regenerate pinned requirements
uv lock
# Commit both pyproject.toml and requirements/*.txt changes
```
### Working with Datasets
**Loading pre-processed datasets (recommended):**
```python
from sec_certs.dataset.cc import CCDataset
dset = CCDataset.from_web() # Downloads from sec-certs.org
```
**Processing from scratch (requires full setup, takes hours, DO NOT DO THIS):**
```bash
uv run sec-certs cc all -o ./dataset
```
## Common Pitfalls and Gotchas
1. **Missing `_version.py`**: Auto-generated by setuptools-scm. Create manually for dev: `echo '__version__ = "dev"' > src/sec_certs/_version.py`
2. **Poppler version**: Ensure Poppler ≥20.x. Version 0.x will cause pdftotext failures.
3. **Spacy model**: ALWAYS run `python -m spacy download en_core_web_sm` after install. Code will fail without it.
4. **Java in PATH**: Required for FIPS table parsing. Verify with `java -version`.
5. **Test markers**: Exclude flaky remote tests with `-m "not remote"` for stable local testing.
6. **Default dataset location**: CLI creates `./dataset` by default. Add to .gitignore if working locally.
7. **Pre-commit hook behavior**: Pre-commit hooks warn about issues but don't auto-fix. Run `ruff check . --fix` to apply fixes.
8. **Long-running commands**: Full dataset processing (`sec-certs cc all`) takes hours. Use pre-processed datasets from web for analysis.
## Additional Resources
- **README.md**: Quick start, installation, basic usage examples
- **CONTRIBUTING.md**: Detailed contribution guidelines, release process, dependency management
- **docs/installation.md**: System dependencies, multiple install methods
- **docs/quickstart.md**: Quick usage examples for CC and FIPS datasets
- **docs/user_guide.md**: Advanced topics (NVD datasets, reference context inference)
- **notebooks/examples/**: Jupyter notebooks demonstrating dataset analysis
- **Website**: https://sec-certs.org (dataset downloads, interactive docs)
- **Documentation**: https://sec-certs.org/docs
## Trust These Instructions
These instructions have been validated by examining repository structure, workflows, documentation, and testing commands. When working on this repository:
1. **Trust these build/test commands** - they are verified to work
2. **Follow the setup order** (system deps → python deps and install (uv sync) → spacy model)
3. **Only search/explore if** these instructions are incomplete or incorrect
4. **Refer to these instructions first** before trying alternative approaches
If you encounter issues not covered here, check CONTRIBUTING.md and docs/ before extensive exploration.
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